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EMAIL SPAM CLASSIFIER

Implemented using Naive Bayes' Algorithm and Deep Learning

Spam emails are unsolicited or junk email that gets sent out in bulk. A classic example of spam emails are emails from so-called Nigerian princes that promise to send you huge amounts of money if you provide them your bank accout details. Spam are annoying because they take up a lot of storage space and communication bandwidth. According to (Awad 2011) “ 40% of all emails are spam which about 15.4 billion email per day and that cost internet users about $355 million per year.” According to (Winder, 2020) “Over half of all global email traffic is spam”. As you can tell, it is a huge problem that needs to be solved.

Both Email Spam Classifier versions were built using Python, NLTK, Bag of Words Model.

View the code for this project on GitHub 

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